• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
• /
• v.9 no.8
• /
• pp.845-854
• /
• 2019

In IoT environment, an intelligent agent is an autonomous entity with computing power that interacts with various things for specific purposes without human intervention. Recently, as the development of Internet technology has increased the size of resources and services that intelligent agents can utilize, an environment where intelligent agents can collaborate with each other is needed. To effectively support these changes, a method is needed to provide workspaces where intelligent agents can form various groups and collaborate on them. In this paper, we present TSpace which is an Ethereum-based group workspace for effective collaboration among intelligent agents. In TSpace, intelligent agents in IoT environment can use group service based on the Ethereum blockchain through the developed CoAP/RESTful web service. TSpace also introduces a new mechanism for managing Ethereum wallets of agents accessing group services and for creating Ethereum transactions using them.

• Journal of the Korean Society of Marine Environment & Safety
• /
• v.27 no.6
• /
• pp.867-874
• /
• 2021

The IoT (Internet of Things) technology is rapidly becoming an important consideration in many engineering fields in the current 4th industrial era. In recent years, the concepts of digital shipbuilding and smart factories have been adopted as trends in shipyards. However, there is active interest in research on implementing autonomous driving in autonomous vehicles and airplanes, which is currently available in commercial form in a limited capacity. The present study is regarding the path-tracking performance of a boat to accomplish an autonomous driving mission using a flight controller (FC) and real-time kinematic (RTK) global positioning system (GPS) based on an open-source Ardupilot; an actual sea test is also performed using this system on a calm lake. The boat's mission is to evaluate the maneuverability of the self-driving process to a specific point and returning to the home position. For a given speed, the difference between the preset mission trajectory and actual operational trajectory was analyzed, and a series of studies were conducted on the applicability of the system to ships. In addition, the movements and maneuverability of the OmniX-type hull with four propellers were investigated, and the driving path-tracking performance was observed to increase by a maximum of 48%.

• Advanced Industrial SCIence
• /
• v.3 no.1
• /
• pp.23-29
• /
• 2024

In this scholarly investigation, the focus is placed on the transformative potential of edge computing in enhancing Intelligent Transportation Systems (ITS) for the facilitation of autonomous driving. The intrinsic capability of edge computing to process voluminous datasets locally and in a real-time manner is identified as paramount in meeting the exigent requirements of autonomous vehicles, encompassing expedited decision-making processes and the bolstering of safety protocols. This inquiry delves into the synergy between edge computing and extant ITS infrastructures, elucidating the manner in which localized data processing can substantially diminish latency, thereby augmenting the responsiveness of autonomous vehicles. Further, the study scrutinizes the deployment of edge servers, an array of sensors, and Vehicle-to-Everything (V2X) communication technologies, positing these elements as constituents of a robust framework designed to support instantaneous traffic management, collision avoidance mechanisms, and the dynamic optimization of vehicular routes. Moreover, this research addresses the principal challenges encountered in the incorporation of edge computing within ITS, including issues related to security, the integration of data, and the scalability of systems. It proffers insights into viable solutions and delineates directions for future scholarly inquiry.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
• /
• 2022.11a
• /
• pp.260-262
• /
• 2022

선박의 전통적인 운항 패턴은 국제적인 기준과 본선의 선장 및 승조원의 역할 수행이 중심이 되지만 자율 운항 선박(Autonomous Ship)에서는 컴퓨터 기반의 시스템과 소프트웨어가 선박의 항해, 기관 정보를 수집하여 상화 인식과 지능형 항로 의사 결정 시스템의 판단에 따라 본선 자체 또는 육상에서의 원격 관제를 통하여 자율운항 모드가 실행이 되어야 한다.. 이 연구에서는 이러한 자율운항 선박의 모든 데이터의 수집과 정보 교환,를 위한 "디지털 브릿지" 플랫폼을 개발하고 시나리오에 기반한 자율운항에 대한 알고리즘을 연구 개발하였다.

• Journal of Internet of Things and Convergence
• /
• v.6 no.2
• /
• pp.31-36
• /
• 2020

The remarkable change in the automobile industry, which is a traditional industrial field, is now evolving into a form of moving toward autonomous functions rather than humans due to various convenience functions and automatic driving or autonomous driving technologies if the person was central when driving the car. This situation is expanding to various industries such as the aviation industry and the drone market, as well as the robot market. The drone market in the aviation industry is being used in various fields due to the unmanned nature of drone operation. Among them, military drones are secret and due to the specificity of technology, details are not disclosed, but as a collection of advanced technologies, they have played a key role in drone development. In this study, the current status of China and the European Union, including the United States, which are major competitors in the drone field, was investigated, and the technologies of major countries were compared and analyzed through the characteristics and operational specifications of the drones currently in operation.

• Journal of the Korea Society of Computer and Information
• /
• v.23 no.11
• /
• pp.159-165
• /
• 2018

In this study, it is analyzed that keywords of the interest in the 4th industrial revolution for science and Technician K women's university students, areas to prioritize in the strategy of 4th industry revolution, to research compare analyze the recognition of science technology such as the most necessary education, human resource development of universities and companies in Korea and abroad according to the technology trend required in the 4th Industrial revolution era and which area to prepare for the 4th industrial revolution. The survey result shows different thoughts of science and Technician(KOFST) and the women university students. In the 1) 4th industrial revolution, the 96% of former are interested, while 60% of latter are interested. And in the most used keywords, the former group used AI(24%), Fusion new industry(21%) the most, while the latter group used AI(34%), Robot(18%). And, 3) in the strategic priority, the science technology experts are interested in education, R&D system innovation(27%), IoT, Information and Communication(26%) and the university students are interested in IoT, Information and Communication(31%), AI(28%). Finally, 4) the science technology experts thought of Autonomous Vehicle(20%), 3D Printer(7%), AI(16%) important, while the women university students thought of AI(27%), VR/Augmented Reality(17%), and Autonomous Vehicle(16%) the most necessary education. In the 4th industrial revolution, we need people with ability to solve complicated problems with creativity based on understanding and absorbing new knowledge and thinking of converged idea.

• KIPS Transactions on Computer and Communication Systems
• /
• v.12 no.3
• /
• pp.93-102
• /
• 2023

Data processing through the cloud causes many problems, such as latency and increased communication costs in the communication process. Therefore, many researchers study edge computing in the IoT, and autonomous driving is a representative application. In indoor self-driving, unlike outdoor, GPS and traffic information cannot be used, so the surrounding environment must be recognized using sensors. An efficient autonomous driving system is required because it is a mobile environment with resource constraints. This paper proposes a machine-learning method using neural networks for autonomous driving in an indoor environment. The neural network model predicts the most appropriate driving command for the current location based on the distance data measured by the LiDAR sensor. We designed six learning models to evaluate according to the number of input data of the proposed neural networks. In addition, we made an autonomous vehicle based on Raspberry Pi for driving and learning and an indoor driving track produced for collecting data and evaluation. Finally, we compared six neural network models in terms of accuracy, response time, and battery consumption, and the effect of the number of input data on performance was confirmed.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2022.10a
• /
• pp.133-135
• /
• 2022

With the development of IoT and AI technologies and media, various digital devices are being used, and unmanned and automation is progressing rapidly. In particular, high-level image processing technology is required in fields such as smart factories, autonomous driving technology, and intelligent CCTV. However, noise present in the image affects processes such as edge detection and object recognition, and causes deterioration of system accuracy and reliability. In this paper, we propose a filtering algorithm using fuzzy weights to reconstruct images damaged by complex noise. The proposed algorithm obtains a reference value using noise judgment and calculates the final output by applying a fuzzy weight. Simulation was conducted to verify the performance of the proposed algorithm, and the result image was compared with the existing filter algorithm and evaluated.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
• /
• v.12 no.6
• /
• pp.567-572
• /
• 2019

In this paper, we propose an algorithm to perform convolution, pooling, and ReLU operations in CNN using binary image and binary kernel. It decomposes 256 gray-scale images into 8 bit planes and uses a binary kernel consisting of -1 and 1. The convolution operation of binary image and binary kernel is performed by addition and subtraction. Logically, it is a binary operation algorithm using the XNOR and comparator. ReLU and pooling operations are performed by using XNOR and OR logic operations, respectively. Through the experiments to verify the usefulness of the proposed algorithm, We confirm that the CNN operation can be performed by converting it to binary logic operation. It is an algorithm that can implement deep running even in a system with weak computing power. It can be applied to a variety of embedded systems such as smart phones, intelligent CCTV, IoT system, and autonomous car.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.28 no.1
• /
• pp.5-14
• /
• 2018

With the advance of the 4th industrial revolution, Internet of Things (IoT) technology is actively being studied. In the era of the IoT, a decentralized operation is required to reduce load on servers and enable autonomous IoT data communication rather than focusing on centralized operation of being server client structures. This paper analyzes the security of a blockchain, a new form of distributed database platform that supports integrity and permanence of data. To achieve this, we divide the blockchain's major operations into a consensus process, network communication process, and key management process, and then describe possible attacks and countermeasures in each process. We also describe the attack occurred in typical cryptocurrency platforms such as Bitcoin and Ethereum.